Leveraging neural network uncertainty in adaptive unscented Kalman Filter for spacecraft pose estimation

This paper introduces an adaptive Convolutional Neural Network (CNN)-based Unscented Kalman Filter for the pose estimation of uncooperative spacecraft. The validation is carried out at Stanford's robotic Testbed for Rendezvous and Optical Navigation on the Satellite Hardware-In-the-loop Rendezvous Trajectories (SHIRT) dataset, which simulates...

IMU-based adaptive filtering for movement artifact removal from ecg recorded with a single lead wearable device

Background and Objectives: Wearable devices (WDs) capable of recording electrocardiograms (ECGs) for prolonged periods in ambulatory settings offer the possibility of detecting non-predictable events such as epileptic seizures and atrial fibrillation. Nevertheless, these systems suffer from additional noise sources, such as movement artifacts ...

Decorrelation in Adaptive Feedback Cancellation for Public Address Systems

Public Address systems that include a setup with at least one microphone and speaker can suffer from acoustic feedback. This results in an annoying howling effect which can damage hardware and human hearing. To solve this issue, an adaptive filter that estimates the feedback path and uses this estimate to cancel the feedback can be designed....

Noise Statistics Estimation based on adaptive filtering

At virtually every public venue, announcements for visitors are made via a public addressing system. It is important that announcements transmitted by means of a public addressing system are not only audible, but also well understood by the general public. This thesis covers one of three subsystems required to make<br/>a product that is capable...

A high-performance and energy-efficient FIR adaptive filter using approximate distributed arithmetic circuits

In this paper, a fixed-point finite impulse response adaptive filter is proposed using approximate distributed arithmetic (DA) circuits. In this design, the radix-8 Booth algorithm is used to reduce the number of partial products in the DA architecture, although no multiplication is explicitly performed. In addition, the partial products are...

On speech enhancement in very low SNRs for smart speakers

Human interaction with a smart speaker involves often distant automatic speech recognition (ASR). However, ASR is a rather cumbersome task at significantly high levels of noise. Most of commercial smart speakers in order to achieve high ASR accuracy they tend to reduce the playback signal once the preset keyword is detected. In an effort to...

3D-LIDAR Multi Object Tracking for Autonomous Driving: Multi-target Detection and Tracking under Urban Road Uncertainties

The recent advancement of the autonomous vehicle has raised the need for reliable environmental perception. This is evident, as an autonomous vehicle has to perceive and interpret its local environment in order to execute reactive and predictive control action. Object Tracking is an integral part of vehicle perception, as it enables the vehicle...

Fault Diagnosis and Fault-Tolerant Control for Aircraft Subjected to Sensor and Actuator Faults

Receding-horizon adaptive contyrol of aero-optical wavefronts

A new method for adaptive prediction and correction of wavefront errors in adaptive optics (AO) is introduced. The new method is based on receding-horizon control design and an adaptive lattice filter. Experimental results presented illustrate the capability of the new adaptive controller to predict and correct aero-optical wavefronts derived...

Adaptive Iterative Learning Control for High Precision Motion Systems

Iterative learning control (ILC) is a very effective technique to reduce systematic errors that occur in systems that repetitively perform the same motion or operation. However, several characteristics have prevented standard ILC from being widely used for high precision motion systems. Most importantly, the learned feedforward signal depends on...

Basis expansion adaptive filters for time-varying system identification

Spatiotonal adaptivity in super-resolution of under-sampled image sequences

This thesis concerns the use of spatial and tonal adaptivity in improving the resolution of aliased image sequences under scene or camera motion. Each of the five content chapters focuses on a different subtopic of super-resolution: image registration (chapter 2), image fusion (chapter 3 and 4), super-resolution restoration (chapter 5), and...

Some aerospace applications of estimation theory

In this report, the application of estimation theory to three problems from aerospace research is described. The applications considered deal with spacecraft attitude estimation, software reliability modelling and estimation, and with a satellite-based navigation algorithm. Maximum likelihood estimation is used in the software reliability case...

Digital filtering methods, with applications to spacecraft attitude determination in the presence of modelling errors. Part II: Extension of theory, and applications

The present issue is the second and final part of a report describing the results of a study about digital filtering. The first part is available as the report NLR TR 760U8 U. The report considers a number of digital filtering methods and gives examples of their application. The methods include batch processing methods and recursive methods....

Processing of Meteosat attitude measurement flight data and evaluation of the performance of an adaptive filtering technique

The attitude measurement data of the ESA geosynchronous spacecraft METEOSAT have been analyzed using an adaptive recursive filtering technique developed at NLR. The mathematical models of spacecraft dynamics and sensors have been kept very simple. Modelling errors are such that, without adaptive feed-back, strong divergence of the filtering...